Advanced Signal Processing Methods for Analysis of Fibrillatory Waves

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Signal processing methods have been used for decades to extract critical information from electrogram recordings of the human heart for diagnosis of numerous heart diseases including atrial fibrillation (AF). AF is the most common cardiac arrhythmia affecting more than 34 million people with an annual cost of $6 billion just in North America. Unfortunately, the current processing methods have had limited success in targeting the sources of AF due to the complex and dynamic nature of the disease. The conventional processing methods used for AF diagnosis are based on sequential data collection and often utilize the local information from individual recording channels to localize AF sources without considering temporal association between the channels to extract wave propagation characteristics. This can be attributed to the fact that the recordings obtained from these systems have low spatial resolution and, due to the sequential acquisition, a global snapshot of fibrillatory waves in atria is not feasible. Recent efforts focus on employing alternative recording equipment to create a panoramic view of the fibrillatory wave propagation in atria. However, the reported outcomes of these studies have been often contradictory. In addition, the high cost and difficulty in placement and maneuvering of these recording devices into small chambers of the heart have prohibited the widespread use of these new diagnostic systems. The aim of my research program is to develop new signal processing methods to study fibrillatory wave propagation in the human heart using data obtained from the conventional recording systems. This will be achieved by developing methods for accurate estimation of local activation intervals and by analyzing the temporal association of local active intervals among simultaneously recorded signals to obtain regional information, in contrast to local information. Although the regional information cannot provide a global wave propagation map in atria, it has an unexplored potential to reveal footprints of the trajectory of the fibrillatory waves and the underlying physiologic properties of the regions within the atria. Our processing methods will be developed and validated by generating realistic simulated data from a detailed 3D model. The applicability of our methods on a clinical database will also be studied. To achieve the goals of this research program, a number of projects will be conducted by five graduate students under my supervision.Successful results from this research program will provide a unique approach to investigate and better understand the propagation of fibrillatory waves using simulated/real sequential data and will facilitate a subsequent study to validate the findings on human data. This can lead to shorter clinical procedures, reduce the financial burden on the Canadian health care system and help the millions of people whose lives are affected by AF.